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» Learning Landmarks for Robot Localization
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IROS
2006
IEEE
128views Robotics» more  IROS 2006»
15 years 3 months ago
Improving Data Association in Vision-based SLAM
— This paper presents an approach to vision-based simultaneous localization and mapping (SLAM). Our approach uses the scale invariant feature transform (SIFT) as features and app...
Arturo Gil, Óscar Reinoso, Óscar Mar...
IJCAI
1997
14 years 11 months ago
Learning Topological Maps with Weak Local Odometric Information
cal maps provide a useful abstraction for robotic navigation and planning. Although stochastic mapscan theoreticallybe learned using the Baum-Welch algorithm,without strong prior ...
Hagit Shatkay, Leslie Pack Kaelbling
ICRA
2008
IEEE
134views Robotics» more  ICRA 2008»
15 years 4 months ago
Towards robust place recognition for robot localization
— Localization and context interpretation are two key competences for mobile robot systems. Visual place recognition, as opposed to purely geometrical models, holds promise of hi...
Muhammad Muneeb Ullah, Andrzej Pronobis, Barbara C...
AROBOTS
2002
91views more  AROBOTS 2002»
14 years 9 months ago
Fast, On-Line Learning of Globally Consistent Maps
To navigate in unknown environments, mobile robots require the ability to build their own maps. A major problem for robot map building is that odometry-based dead reckoning cannot ...
Tom Duckett, Stephen Marsland, Jonathan Shapiro
CRV
2006
IEEE
192views Robotics» more  CRV 2006»
15 years 1 months ago
Design and analysis of a framework for real-time vision-based SLAM using Rao-Blackwellised particle filters
This paper addresses the problem of simultaneous localization and mapping (SLAM) using vision-based sensing. We present and analyse an implementation of a RaoBlackwellised particl...
Robert Sim, Pantelis Elinas, Matt Griffin, Alex Sh...